Support vector machine based optimization of multi-fault classification of gears with evolutionary algorithms from time-frequency vibration data

Measurement: Journal of the International Measurement Confederation

Volumn 55, Issue , 2014, Pages 1-14

  Bordoloi, D J ^a   Tiwari, Rajiv ^a  

^a INDIAN INSTITUTE OF TECHNOLOGY GUWAHATI   (India)

Author keywords

Interpolation and extrapolation; Multi fault classification; Optimization; Support vector machine; Wavelets

Indexed keywords

ALGORITHMS; EXTRAPOLATION; GEARS; GENETIC ALGORITHMS; OPTIMIZATION; WAVELET TRANSFORMS;

ARTIFICIAL BEE COLONY ALGORITHMS; CLASSIFICATION ABILITY; CONTINUOUS WAVELET TRANSFORMS; FAULT CLASSIFICATION; PREDICTION PERFORMANCE; STATISTICAL FEATURES; WAVELET PACKET TRANSFORM(WPT); WAVELETS;

SUPPORT VECTOR MACHINES;

EID: 84901032570     PISSN: 02632241     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.measurement.2014.04.024     Document Type: Article

References (45)

1. J.F.A. Leblanc, J.R.F. Dube, B. Devereux. Helicopter Gearbox Vibration Analysis in the Canadian Forces - Applications and Lessons, in: Proceedings of the first international conference, gearbox noise and vibration, IMechE Cambridge, UK, 1990, pp. 173-177.
2. B.G. Cameron, M.J. Stuckey, A Review of Transmission Vibration monitoring at Westland Helicopter Ltd, in: Proceedings of the 20th European Rotorcraft Forum, 1994, pp. 16-116.
3. J.I. Taylor Back to the basics of rotating machinery vibration analysis Sound Vib. 29 2 1995 12 16
4. C.J.C. Burgess A tutorial on support vector machines for pattern recognition Data Min. Knowl. Disc. 2 1998 955 974
5. Z.K. Peng, and F.L. Chu Application of the wavelet transform in machine condition monitoring and fault diagnostics: a review with bibliography Mech. Syst. Signal Process. 18 2004 199 221
6. Achmad Widodo, and Bo-Suk Yang Support vector machine in machine condition monitoring and fault diagnosis Mech. Syst. Signal Process. 21 2007 2560 2574
7. W.J. Wang, and P.D. Mcfadden Early detection of gear failure by vibration analysis II: interpretation of the time-frequency distribution using image processing techniques Mech. Syst. Signal Process. 7 3 1983 205 215
8. L.B. Jack, and A.K. Nandi Fault detection using support vector machines and artificial neural networks, augmented by genetic algorithms Mech. Syst. Signal Process. 16 2-3 2002 373 390
9. B. Samanta Gear fault detection using artificial neural networks and support vector machines with genetic algorithms Mech. Syst. Signal Process. 18 2004 625 644
10. Jianping Xuan, Hanhong Jiang, Tielin Shi, and Guanglan Liao Gear fault classification using genetic programming and support vector machines Int. J. Inf. Technol. 9 2005 19 27
11. S. Liu, C.-Y. Jia, H. Ma. A new weighted Support Vector Machine with GA-Based Parameter Selection. In: Proceedings of the Fourth International Conference on Machine Learning and Cybernetic, 2005, Guangzhou, 18-21 August 2005.
12. S.A. Rajas, D. Fernandez-Reyes. Adapting Multiple Kernel Parameters for Support Vector Machines using Genetic Algorithms, IEEE Congress on Evolutionary Computation (CEC-2005), 2005, pp. 626-631.
13. C.-L. Huang, and C.-J. Wang A GA-based feature selection and parameters optimization for support vector machines Expert Syst. Appl. 31 2006 231 240
14. N. Saravanan, V.N.S. Kumar Siddabattuni, and K.I. Ramachandran A comparative study on classification of features by SVM and PSVM extracted using Morlet wavelet for fault diagnosis of spur bevel gear box Expert Syst. Appl. 35 2008 1351 1366
15. Cheng Junsheng, Yu Dejie, and Yang Yu A fault diagnosis approach for gears based on IMF AR model and SVM EURASIP J. Adv. Signal Process. 2008 1 7
16. R. Tiwari, N. Tanwar, S. Mishra, Application of support vector machine techniques for heath monitoring of gears. National Conference on Condition Monitoring (NCCM-2009), NSTL, Visakhapatnam, India, 2009.
17. N. Saravanan, S. Cholairajan, and K.I. Ramachandran Vibration-based fault diagnosis of spur bevel gear box using fuzzy technique Expert Syst. Appl. 36 2009 3119 3135
18. S. Ali, J.M. Mohammad, S. Masoud, Fault classification in gears using support vector machines (SVMs) and signal processing. IEEE Transaction, 2009, 9781-4244-3428-2/09.
19. Lixin Gao, Zhiqiang Ren, Wenliang Tang, Huaqing Wang, and Peng Chen Intelligent gearbox diagnosis methods based on SVM, wavelet lifting and RBR J. Sens. 10 2010 4602 4621
20. A.H. Zamanian, A. Ohadi, Gearbox Fault Detection Through PSO Exact Wavelet Analysis and SVM Classifier, in: 18th Annual International Conference on Mechanical Engineering-ISME 2010, Sharif University of Technology, Tehran, Iran, 2010.
21. F. Samadzadegan, A. Soleymani, R.R. Ali Abbaspour. Evaluation of Genetic Algorithms for Tuning SVM Parameters in Multi-Class Problems, in: 11th IEEE International Symposium on Computational Intelligence and Informatics, 18-20 November, 2010, Budapest, Hungary, 2010.
22. D.J. Bordoloi, and R. Tiwari Optimization of support vector machine based multi-fault classification with evolutionary algorithms from the time domain vibration data of gears Proc. Inst. Mech. Eng. Part C: J Mech. Eng. Sci. 2013 10.1177/0954406213477777
23. D.J. Bordoloi, and R. Tiwari Optimum multi-fault classification of gears with integration of evolutionary and SVM algorithms Mech. Mach. Theory 73 2014 49 60
24. S. Mallat A Wavelet Tour of Signal Processing 1998 Academic Press
25. S. Mallat A theory for multiresolution signal decomposition: the wavelet representation IEEE Pattern Anal. Machine Intell. 11 7 1989 674 693
26. K.P. Soman, and K.I. Ramachandran Insight Into Wavelets From Theory to Practice 2005 Prentice-Hall of India Private Limited
27. R.R. Coifman, and M.V. Wickerhauser Entropy-based algorithms for best basis selection IEEE Trans. Inform. Theory 38 2 1992 713 718
28. J. Rafiee, P.W. Tse, A. Harifi, and M.H. Sadeghi A novel technique for selecting mother wavelet function using an intelligent fault diagnosis system Expert Syst. Appl. 36 2009 4862 4875
29. W.J. Wang, and P.D. McFadden Application of orthogonal wavelets to early gear damage detection Mech. Syst. Signal Process. 9 5 1995 497 507
30. V.N. Vapnik The Nature of Statistical Learning Theory 1995 Springer New York
31. C. Cortes, and V. Vapnik Support-vector network Machine Learning 20 1995 273 297
32. B.E. Boser, I. Guyon, V. Vapnik, A Training Algorithm for Optimal Margin Classifiers, in: Proceedings of the Fifth Annual Workshop on Computational Learning Theory, ACM Press, 1992, pp. 144-152.
33. B. Scholkopf, A. Smola, R.C. Williamson, and P.L. Bartlett New support vector algorithms Neural Comput. 12 2000 1207 1245
34. S. Knerr, L. Personnaz, G. Dreyfus, Single-layer learning revisited: a stepwise procedure for building and training a neural network. Neurocomputing: Algorithms, Architectures and Applications, NATO ASI, Springer-Verlag, Berlin, 1990, pp. 41-50.
35. U.H.G. Kressel, Pairwise classification and support vector machines, in: B. Scholkopf, C.J.C. Burges, A.J. Smola (Eds.), Advances in Kernel Methods-Support Vector Learning, MIT Press, Cambridge, MA, 1998, pp. 255-268.
36. C.-W. Hsu, and C.-J. Lin A comparison of methods for multi-class support vector machines IEEE Trans. Neural Networks 13 2 2002 415 425
37. C.-C. Chang, C.-J. Lin, LIBSVM: A library for support vector machines. ACM Transactions on Intelligent Systems and Technology, 2011, 2:27:1-27:27. http://www.csie.ntu.edu.tw/~cjlin/libsvm.
38. LIBSVM (2011), Version 3.1. http://www.csie.ntu.edu.tw/~cjlin/libsvm.
39. K. Deb Multi-Objective Optimization Using Evolutionary Algorithms 2003 John Willey & Sons Ltd Chichester
40. K. Deb Optimization for Engineering Design: Algorithms and Examples 1995 Printice-Hall of India Pvt. Ltd New Delhi
41. C.R. Houck, J. Joines, M. Kay, A genetic algorithm for function optimization: A Matlab implementation. ACM Transactions on Mathematical Software, 1996. http://www.ise.ncsu.edu/kay.
42. GA software website http://www.ise.ncsu.edu/kay/.
43. D. Karaboga, and B. Basturk A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm J. Global Optim. 39 3 2007 171 459 http://www.mf.erciyes.edu.tr/abc
44. D. Karaboga, and B. Basturk On the performance of artificial bee colony (ABC) algorithm Appl. Soft Comput. 8 1 2008 687 697
45. ABC algorithm MATLAB (2009), Version 2, http://www.mf.erciyes.edu.tr/abc.